The Cost of Big Brains in Groups

Nagar, Danielle; Furman, Alexander; Nitschke, Geoff

doi:10.1162/isal_a_00193

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…This might make conclusions about task-related neural complexity as opposed to task-independent complexity not entirely justified. However, related work by Nagar et al (2019) that did include a behavioral task found results similar to ours.…”

Section: Discussionsupporting

confidence: 89%

Shrunken Social Brains? A Minimal Model of the Role of Social Interaction in Neural Complexity

Reséndiz-Benhumea

Sangati

et al. 2021

Front. Neurorobot.

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The social brain hypothesis proposes that enlarged brains have evolved in response to the increasing cognitive demands that complex social life in larger groups places on primates and other mammals. However, this reasoning can be challenged by evidence that brain size has decreased in the evolutionary transitions from solitary to social larger groups in the case of Neolithic humans and some eusocial insects. Different hypotheses can be identified in the literature to explain this reduction in brain size. We evaluate some of them from the perspective of recent approaches to cognitive science, which support the idea that the basis of cognition can span over brain, body, and environment. Here we show through a minimal cognitive model using an evolutionary robotics methodology that the neural complexity, in terms of neural entropy and degrees of freedom of neural activity, of smaller-brained agents evolved in social interaction is comparable to the neural complexity of larger-brained agents evolved in solitary conditions. The nonlinear time series analysis of agents' neural activity reveals that the decoupled smaller neural network is intrinsically lower dimensional than the decoupled larger neural network. However, when smaller-brained agents are interacting, their actual neural complexity goes beyond its intrinsic limits achieving results comparable to those obtained by larger-brained solitary agents. This suggests that the smaller-brained agents are able to enhance their neural complexity through social interaction, thereby offsetting the reduced brain size.

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Section: Discussionsupporting

confidence: 89%

Shrunken Social Brains? A Minimal Model of the Role of Social Interaction in Neural Complexity

Reséndiz-Benhumea

Sangati

et al. 2021

Front. Neurorobot.

View full text Add to dashboard Cite

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“…Now, the question of how to operationalize this dependent variable is by no means straightforward. The simplest measure such as the number of neurons (used, for instance in a related study by Nagar et al, 2019) does not seem appropriate because a smaller brain can in principle be more cognitively efficient than a bigger brain, depending on its organization and its embedding in a particular task environment. In the field of biological complexity, a great variety of more general measures have been proposed, many of which focus on whether some time series produced by the organism shows signs of an underlying chaotic process (Adami, 2002).…”

Section: Introductionmentioning

confidence: 99%

Evolution of Neural Complexity in Division of Labor Tasks

Sangati¹,

Keshmiri²,

Sangati³

2021

The 2021 Conference on Artificial Life

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We evolve artificial agents to perform a simple tracking task in three conditions: one individual (Isolated Condition) and two joint action conditions with division of labor. The joint conditions differ by whether two agents switch complementary roles during the task (Generalist Condition) or always play the same role (Specialist Condition). At the end of evolutionary runs we calculate the agents' neural complexity using Tononi-Sporns-Edelman (TSE) complexity measure which relates to Integrated Information Theory (IIT). We show that (1) division of labor with specialization leads to a level of neural complexity comparable to the complexity of performing the same task alone, and that (2) both are lower than neural complexity when performing the task jointly with role switching. We further consider viewing collaborating agents as a single extended system and calculate its joint neural complexity. We demonstrate that contrary to our predictions, the same pattern of results, i.e., Generalists' complexity being higher than Specialists', holds also in this conceptualization.

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Energy and Complexity in Evolving Collective Robot Bodies and Brains

Hallauer

Nitschke

2020

2020 IEEE Congress on Evolutionary Computation (CEC)

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The Cost of Big Brains in Groups

Cited by 4 publications

References 24 publications

Shrunken Social Brains? A Minimal Model of the Role of Social Interaction in Neural Complexity

Shrunken Social Brains? A Minimal Model of the Role of Social Interaction in Neural Complexity

Evolution of Neural Complexity in Division of Labor Tasks

Energy and Complexity in Evolving Collective Robot Bodies and Brains

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